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    UniMAP loT : Android based facial image recognition using neural networks for class attendance truancy

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    UniMAP loT - Android based facial image recognition using neural networks for class attendance truancy.pdf (7.003Mb)
    Date
    2015-04-17
    Author
    Wan Hafidzoh, Megat Adnan
    Nur Suhana, Ismail
    Mohd Razif, Mustafa
    Hairunisa, Md Hanapi
    Muhammad Ezanuddin, Abd Aziz
    Norfazlin, Rashid
    Abd Hafiizh, Ismail
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    Abstract
    Following any conventional Malaysia universities, lecturers take attendance by calling out the names of students, and then marking them, while, in others, lecturers pass around a sheet of paper, asking students to sign in attendance sheet. Both practices have their drawbacks. In the first case, if numerous groups attend the lesson, checking all of these students by name might take about several minutes out of each lesson; in the second case, friends of absent students may write down their names. These practices place university lecturers and their institutions at considerable disadvantages when it comes to taking attendance. To rectify these systematic failings, this project intend to use Android (an open source OS) coupled with neural network working algorithm for face recognition purposes via each lecturers smartphones.
    URI
    http://dspace.unimap.edu.my:80/xmlui/handle/123456789/40444
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